Expand description
Complex Wavelets Module
Complex wavelets provide both magnitude and phase information, making them ideal for analyzing non-stationary financial time series where phase relationships and instantaneous frequency are important.
§Key Features
- Complex Morlet: Optimal time-frequency localization for trend analysis
- Complex Mexican Hat: Good for detecting singularities and discontinuities
- Complex Paul: Specialized for detecting oscillatory patterns
- Analytic Wavelets: Phase-preserving decomposition for financial signals
§Financial Applications
- Trend Analysis: Phase information reveals trend strength and direction
- Regime Detection: Instantaneous frequency changes indicate regime shifts
- Volatility Clustering: Phase coherence identifies volatility periods
- Lead-Lag Analysis: Cross-wavelet phase relationships between assets
§See Also
- Wavelet families and how to choose discrete wavelets:
docs/WAVELET_FAMILIES.md - Transform behavior (CWT and dual-tree CWT):
docs/TRANSFORMS_GUIDE.md - Advanced analysis (coherence using ComplexMorlet and other complex wavelets):
docs/ADVANCED_ANALYSIS.md
Structs§
- Complex
Mexican Hat - Complex Mexican Hat (Ricker) Wavelet
- Complex
Morlet - Enhanced Complex Morlet Wavelet for Financial Analysis
- Complex
Paul - Complex Paul Wavelet
- Complex
Wavelet Result - Complex Wavelet Analysis Result